Remote image acquisition by camera systems has become a ubiquitous and invasive feature of modern life. To note a few of the applications to which remote image acquisition is employed, remote camera systems are used to watch our streets, guard the entrances to our buildings, monitor internal venues of our malls, survey global vegetation patterns, track global weather, and guide remote and autonomous piloted ground and airborne vehicles. Remote images of a region of interest (ROI) of an environment acquired by a remote camera system may be processed by a computer system and/or monitored by a human to detect and/or respond to “events of note” that transpire or are encountered in the ROI. An event of note may be any of various events for which a computer system or human may advantageously be expected to provide an active or passive response, such as respectively an overt action or a change of level of attention. An event of note in an ROI imaged by a remote camera may, by way of example, comprise a statistically aberrant event within the ROI, suspicious human or vehicular motion in the ROI, entry of a migrating flock of geese into the ROI, or an encounter of an obstacle in the ROI by a remote piloted or auto-piloted vehicle.
Efficiency of detection for events of note in an ROI responsive to remote images of the ROI may be compromised by artifacts in the images that degrade quality of the images and mask or draw attention away from events of note. Image artifacts in remote ROI images generally increase processing time that computer algorithms require for processing the images to detect images of events of note they may contain, and reduce reliability of results provided by the algorithms. Image artifacts in ROI images displayed as a continuous video sequence on a computer screen for visual monitoring by a human operator may generate not only distortions in the images but also poor registration between consecutive images in the sequence. The distortions and degraded registration tend to accelerate operator fatigue and impair his or her sensitivity for detecting events of note in the ROI that may appear in the images.
Image artifacts may be introduced into remote images of an ROI by features associated with the remote camera system that acquires the images and how the remote camera system is configured and used to image the ROI. Image artifacts may include image distortions generated by camera angle, optical system aberrations, and defocus blur.
For camera systems mounted to a moving platform, such as a ground or an airborne vehicle, to acquire surveillance images of an ROI, image artifacts may be exacerbated and additional image artifacts introduced into the remote images by motion of the camera system during acquisition of the remote images. Motion artifacts can be generated by planned motion of the platform and/or disturbances to planned motion of the platform that erratically shift the remote camera system field of view (FOV) relative to the ROI.
Planned motion of a ground vehicle comprises intended motion of the ground vehicle along a planned ground route. Disturbances to the ground vehicle motion may be generated by vibrations of its power train or by unanticipated lurching and bouncing of the ground vehicle as it travels along the planned route. For the increasingly frequent situation in which a remote camera system is mounted to an airborne vehicle, such as an unmanned aerial vehicle (UAV), an airship, or an aerostat, for weather, environmental, or security surveillance monitoring, planned motion of the airborne vehicle comprises motion along an intended flight path. For a heliostat, which is tethered, an intended flight path is considered to include hovering in a region of sky to which motion of the heliostat is limited by a tether. Disturbance to the planned motion may be generated for example by vibrations of the airborne vehicle propulsion system, and/or air turbulence.
To moderate motion artifacts generated in remote images of an ROI acquired by an airborne remote camera system, the remote camera system is generally mounted to an airborne vehicle by a two or three axis gimbaled mount. An inertial measurement unit (IMU) provides measurements of displacement of the platform along optionally three orthogonal “displacement axes”, and rotation of the platform about, optionally three orthogonal “rotation axes”. The measurements are processed to determine “dead reckoning” position and orientation of the platform. A controller controls the gimbaled mount responsive to the measurements of position and orientation to counter motion of the platform and stabilize the location and orientation of the ROI within the camera system FOV. Dead reckoning position and orientation are subject to substantial drift error over time and are typically calibrated to, or “fused with”, measurements provided by GNSS (global navigation satellite system) equipment and magnetometers, which may be included in the IMU.
High resolution airborne camera systems may have angular resolutions that are less than or equal to about 20 or 30 microradians and may operate to acquire images of large terrestrial areas equal to or greater than about 1 km square from altitudes of between 5 and 6 km. At an altitude of about 5 km, a high resolution airborne camera system having angular resolution between 20 and 30 microradians may acquire terrestrial images that resolve features on the ground that are separated by as little as 10 and 15 cm. Whereas pedestrian airborne camera systems may be sufficiently stabilized by two or three axes gimbaled mounts such high resolution camera systems conventionally require that their cameras be mounted to particularly robust and fast response gimbaled mounts for stabilizing camera orientation during remote airborne imaging. The gimbaled camera mounts of these systems tend to be mechanically complex, relatively large, massive, and expensive.
For example, a gimbaled camera mount for stabilizing orientation of a high resolution airborne camera for imaging relatively large land areas at a resolution of about 20-30 microradians may weigh in excess of 100 kg-200 kg (kilogram). The gimbaled camera mount generally comprises an IMU sensor that provides measurements of platform translation and rotation and a gimbal system comprising a fast response, high resolution gimbal nested in and supported by a slower, course resolution gimbal. The high resolution gimbal typically provides rapid, fine rotational correction of camera orientation about three orthogonal rotation axes for relatively small angular dynamic ranges of up to about 2°. The coarse gimbal provides slower rotational corrections of camera orientation about the axes for dynamic ranges of tens of degrees.